摘要
针对液压弯辊控制系统的时变性、非线性和不确定性等特点,设计利用G A(遗传算法)优化的P I D神经网络(P I D N N)液压弯辊控制系统。P I D N N控制器不仅具有不依赖被控对象数学模型的优点,而且有很好的动态性能,结构简单易于设计。利用G A代替B P算法对P I D N N权值进行优化,克服了B P算法易陷于局部极小的不足。2种优化方法的仿真结果对比表明:G A-P I D N N控制器能够使液压弯辊力快速达到目标值,并且具有较强的抗干扰能力。
According to the characteristics of time-varying,nonlinear,and the uncertainty of the hydraulic roll bending control system,a hydraulic roll bending control system based on PIDNN（PID neural network）optimized by GA（genetic algorithm）was proposed.PIDNN controller has the advantage of simple structure and good dynamic performance,which is easy to design and does not rely on the mathematical model of control led object.Inorder to overcome BP algorithm＇s short age of easy trapped in local minimum,GA was used to optimize the weights of PIDNN instead of BP algorithm.The comparative simulation results of these two optimization methods demon strate that GA-PIDNN controller can make hydrauli croll bending force quickly reach the target and has a good ability of anti-disturbance.
出处
《中南大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2014年第11期3800-3804,共5页
Journal of Central South University:Science and Technology
基金
国家自然科学基金资助项目(50675186)~~
